So Rita, Vingarzan Roxanne, Jones Keith, Pitchford Marc
a Air Quality Science Unit, Prediction Services Operations West, Meteorological Services of Canada, Environment Canada , Vancouver , British Columbia , Canada.
J Air Waste Manag Assoc. 2015 Jun;65(6):707-20. doi: 10.1080/10962247.2015.1010750.
Fine particulate matter (PM2.5) is the dominant cause of atmospheric visibility degradation in the Lower Fraser Valley (LFV) of British Columbia, where poor visibility due to air pollution is of concern. The spatial coverage of the current LFV visibility monitoring network is relatively low, with large parts of the airshed not being represented. Given the desire on the part of local and regional governments to manage visibility in the LFV airshed, the development of a method that allows near real-time estimation of 1-hr light extinction data from the dense network of PM measurements would be highly beneficial. This paper describes a simple linear algorithm, developed using the Hybrid method, to estimate near real-time 1-hr total light extinction at four monitoring sites in the LFV. Model inputs include ambient hourly PM2.5, NO2, relative humidity measurements, and historical monthly-averaged aerosol composition. The results indicate that the developed model can provide relatively accurate and time-resolved estimates of extinction in regions where visibility is not being monitored, thus extending the spatial coverage of the regional visibility monitoring network. The model was also applied to a number of policy-related scenarios to inform visual air quality management in the study area. Results indicated that in order to achieve a perceptible improvement (1.0 deciview) relative to baseline average visibility conditions in the LFV airshed, average ambient PM2.5 concentration would have to decrease by 17% from baseline conditions. Furthermore, to achieve a 20% increase in the number of daylight hours with "excellent" visibility, average PM2.5 would need to be reduced by 30%. Model simulations also indicated that "across-the-board" emission reduction policies would result in greater improvements for the "worst 20%" visibility conditions than for the "best 20%" conditions, suggesting that reducing the number of "poor" visibility days would be easier than improving the number of "excellent" visibility days.
This study describes the development of a model using standard air quality monitoring data (PM2.5, NO2, relative humidity, and PM speciation profiles) to provide near real-time estimates of time-resolved extinction in regions where direct optical monitoring is not available. Applications of the model include extension of spatial coverage of a visibility network, testing various air quality scenarios to inform visibility management, and as a tool for setting visual air quality standards in impacted airsheds.
细颗粒物（PM2.5）是不列颠哥伦比亚省低弗雷泽河谷（LFV）大气能见度下降的主要原因，该地区空气污染导致的能见度差令人担忧。当前LFV能见度监测网络的空间覆盖范围相对较低，大部分空气流域未被覆盖。鉴于地方和地区政府希望管理LFV空气流域的能见度，开发一种能够根据密集的PM测量网络近乎实时估算1小时光消光数据的方法将非常有益。本文描述了一种使用混合方法开发的简单线性算法，用于估算LFV四个监测站点的近乎实时1小时总光消光。模型输入包括每小时的环境PM2.5、NO2、相对湿度测量值以及历史月平均气溶胶成分。结果表明，所开发的模型能够在未进行能见度监测的区域提供相对准确且具有时间分辨率的消光估算，从而扩展了区域能见度监测网络的空间覆盖范围。该模型还应用于一些与政策相关的情景，为研究区域的视觉空气质量管理提供信息。结果表明，为了相对于LFV空气流域的基线平均能见度条件实现可感知的改善（1.0 分贝视角），平均环境PM2.5浓度必须比基线条件降低17%。此外，为了使“极佳”能见度的白天小时数增加20%，PM2.5平均浓度需要降低30%。模型模拟还表明，“全面”减排政策对“最差20%”能见度条件的改善将比对“最佳20%”条件的改善更大，这表明减少“差”能见度天数比增加“极佳”能见度天数更容易。
本研究描述了一种利用标准空气质量监测数据（PM2.5、NO2、相对湿度和PM形态分布）开发的模型，用于在无法进行直接光学监测的区域提供近乎实时的时间分辨消光估算。该模型的应用包括扩展能见度网络的空间覆盖范围、测试各种空气质量情景以指导能见度管理，以及作为在受影响空气流域设定视觉空气质量标准的工具。
